Management of soil cover and tillage regimes in upland rice-sweet corn systems for better system performance, energy use and carbon footprints.

This study investigates the effects of tillage and mulching regimes on rice-sweet corn systems in the lower Gangetic plains, focusing on region-specific and crop-specific impacts on soil-crop-environmental parameters. The experiment consisted of three levels of tillage: conventional (CT), minimum (MT), and zero (ZT), and four levels of mulching: live, leaf litter, paddy straw, and no mulching. The results show that ZT tillage resulted in higher bulk density (BD) compared to other treatments, despite an increase in soil organic carbon (SOC). Live and leaf litter mulching led to slight reductions in BD in the upper soil layers. CT resulted in net depletion of SOC whereas ZT registered a positive sequestration rate of 1.19 Mg ha-1 yr-1. Live and leaf litter mulching increased SOC sequestration by 42.6% and 38.8% compared to paddy straw mulching, respectively. Initially, ZT resulted in a 10.3% reduction in system productivity compared to CT, while MT yields were comparable to CT. However, mulching regimes consistently improved production by 16.4%-25.2% as compared to no mulch. ZT and MT were found to be more affordable than CT, with cost savings of 18.2% and 6.8%, respectively. ZT had the highest B: C ratio, indicating better economic efficiency. Among the mulching treatments, live mulching was the most economical. Both ZT and MT saved input energy by approximately 22.9% and 13.5%, respectively compared to CT. Live mulching resulted in the highest net energy and energy output. Compared to CT, ZT reduced carbon footprint (CF) by 41.5 and 22.2% in rice and sweet corn, respectively. MT scored midway between ZT and CT in all parameters. CT exhibited several limitations, including high input energy requirements, high cost of cultivation, poor economic efficiency, negative environmental impacts, and loss of SOC. ZT initially experienced yield reduction and lower net returns in the early years. Therefore, MT was identified as the best alternative in the initial years before transitioning completely to ZT, as it provided comparable yields to CT with better overall benefits. Among the soil cover regimes, live mulching was found to be the most favorable option across all dimensions.

The assessment of reservoir potential of Permian to Eocene reservoirs of Minwal-Joyamair fields, upper Indus basin, Pakistan.

Upper Indus Basin has been a valuable asset as the complexity of structure and hydrocarbon production is the leading producer of oil and gas in history and still to date. Potwar sub-basin has significance in the light of oil production from carbonate reservoirs or Permian to Eocene age reservoirs. Minwal-Joyamair field is very significant and has unique hydrocarbon production history with complexity in structure style and stratigraphy. The complexity is present for carbonate reservoirs of the study area due to heterogeneity of lithological and facies variation. In this research, the emphasis is on integrated advanced seismic and well data for Eocene (Chorgali, Sakesar), Paleocene (Lockhart), and Permian age (Tobra) formations reservoirs. This research's primary focus is to analyze field potential and reservoir characterization by conventional seismic interpretation and petrophysical analysis. Minwal-Joyamair field is a combination of thrust and back thrust, forming a triangle zone in the subsurface. The petrophysical analysis results suggested favorable hydrocarbon saturation in Tobra (74%) and Lockhart (25%) reservoirs in addition to the lower volume of shale (28% and 10%, receptively) and higher effective values (6% and 3%, respectively). The main objective of the study is the re-assessment of a hydrocarbon producing field and describe the future prospectively of the field. The analysis also includes the difference in hydrocarbon production from two different type of reservoir (carbonate & clastic). The findings of this research will be useful for any other similar basins around the world.

Pollution Vulnerability of the Ghiss Nekkor Alluvial Aquifer in Al-Hoceima (Morocco), Using GIS-Based DRASTIC Model.

Groundwater resources of the alluvial aquifer Ghiss Nekkor, which covers an area of 100 km2, are the main source of domestic and agricultural freshwater supply in the region of Al Hoceima in Morocco. Due to human activities (overexploitation, increase in agricultural activity), this alluvial aquifer has become very sensitive to chemical pollution. The principal objective of this current study is to develop and implement a calibration method to assess, map, and estimate the vulnerability of the Ghiss Nekkor alluvial aquifer to pollution risk. In this work, the GIS-based DRASTIC model was used to estimate the inherent vulnerability to contamination of the Ghiss Nekkor alluvial aquifer with seven standard hydrogeological parameters. Nitrate (NO3) and electrical conductivity (EC) data were used to validate the DRASTIC map. The results of the vulnerability map analysis show that the vulnerability to contaminants varies from non-existent in the southwestern part of the plain (7.3% of the total area), to very high (14.5%). The vulnerability is moderate in the central and northeastern areas (26.9%), while it is high in the other areas (17.5%). Furthermore, the most sensitive areas are mainly concentrated near the coastal strip and the central plain on both sides of the Nekkor River. In these areas, the NO3 and EC values are above the maximum allowable limit of the World Health Organization. The results suggest that the DRASTIC model can be an effective tool for decision-makers concerned about managing groundwater sustainability.

Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling.

The Meyal oil field (MOF) is among the most important contributors to Pakistan's oil and gas industry. Northern Pakistan's Potwar Basin is located in the foreland and thrust bands of the Himalayan mountains. The current research aims to delineate the hydrocarbon potential, reservoir zone evaluation, and lithofacies identification through the utilization of seven conventional well logs (M-01, M-08, M-10, M-12, M-13P, and M-17). We employed the advanced unsupervised machine-learning method of self-organizing maps for lithofacies identification and the novel Quanti Elan model technique for comprehensive multimineral evaluation. The shale volume, porosity, permeability, and water saturation (petrophysical parameters) of six wells were evaluated to identify the reservoir potential and prospective reservoir zones. Well-logging data and self-organizing maps were used in this study to provide a less costly method for the objective and systematic identification of lithofacies. According to the SOM and Pickett plot analyses, the zone of interest is mostly made up of pure limestone oil zone, whereas the sandy and dolomitic behavior with a mixture of shale content shows non-reservoir oil-water and water zones. The reservoir has good porosity values that range from 0 to 18%, but there is a high water saturation of up to 45% in reservoir production zones. The presence of shale in the entire reservoir interval has a negative effect on the permeability value, but the petrophysical properties of the Meyal oil reservoir are good enough to permit hydrocarbon production. According to the petrophysical estimates, the Meyal oil field's Sakesar and Chorgali Formations are promising reservoirs, and new prospects for drilling wells in the southern and central portions of the eastern portion of the research area are recommended.